메뉴 건너뛰기




Volumn 44, Issue 10, 2017, Pages 1721-1742

Stochastic correlation coefficient ensembles for variable selection

Author keywords

LASSO; maximal relevance; minimal redundancy; ranking; stochastic correlation coefficient ensemble

Indexed keywords


EID: 84982162233     PISSN: 02664763     EISSN: 13600532     Source Type: Journal    
DOI: 10.1080/02664763.2016.1221913     Document Type: Article
Times cited : (6)

References (48)
  • 1
    • 84937976706 scopus 로고    scopus 로고
    • A mutual association based nonlinear ensemble mechanism for time series forecasting
    • R., Adhikari, A mutual association based nonlinear ensemble mechanism for time series forecasting, Appl. Intell. 43 (2015), pp. 233–250. doi:10.1007/s10489-014-0641-y
    • (2015) Appl. Intell. , vol.43 , pp. 233-250
    • Adhikari, R.1
  • 2
    • 0028468293 scopus 로고
    • Using mutual information for selecting features in supervised neural net learning
    • R., Battiti, Using mutual information for selecting features in supervised neural net learning, IEEE Transact Neural Netw. 5 (1994), pp. 537–550. doi:10.1109/72.298224
    • (1994) IEEE Transact Neural Netw. , vol.5 , pp. 537-550
    • Battiti, R.1
  • 3
    • 84939948968 scopus 로고    scopus 로고
    • An information-theoretic framework for improving imperfect dynamical predictions via multi-model ensemble forecasts
    • M., Branicki and A.J., Majda, An information-theoretic framework for improving imperfect dynamical predictions via multi-model ensemble forecasts, J. Nonlinear Sci. 25 (2015), pp. 489–538. doi:10.1007/s00332-015-9233-1
    • (2015) J. Nonlinear Sci. , vol.25 , pp. 489-538
    • Branicki, M.1    Majda, A.J.2
  • 4
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • L., Breiman, Random forests, Mach. Learn. 45 (2001), pp. 5–32. doi:10.1023/A:1010933404324
    • (2001) Mach. Learn. , vol.45 , pp. 5-32
    • Breiman, L.1
  • 5
    • 84901935441 scopus 로고    scopus 로고
    • A comparison of simulated annealing algorithms for variable selection in principal component analysis and discriminant analysis
    • M.J., Brusco, A comparison of simulated annealing algorithms for variable selection in principal component analysis and discriminant analysis, Comput. Stat. Data Anal. 77 (2014), pp. 38–53. doi:10.1016/j.csda.2014.03.001
    • (2014) Comput. Stat. Data Anal. , vol.77 , pp. 38-53
    • Brusco, M.J.1
  • 6
    • 84919630495 scopus 로고    scopus 로고
    • Feature selection using a neural framework with controlled redundancy
    • R., Chakraborty and N.R., Pal, Feature selection using a neural framework with controlled redundancy, IEEE Trans. Neural Netw. Learn. Syst. 26 (2015), pp. 35–50. doi:10.1109/TNNLS.2014.2308902
    • (2015) IEEE Trans. Neural Netw. Learn. Syst. , vol.26 , pp. 35-50
    • Chakraborty, R.1    Pal, N.R.2
  • 7
    • 72049084727 scopus 로고    scopus 로고
    • Modeling wine preferences by data mining from physicochemical properties
    • P., Cortez, A., Cerdeira, F., Almeida, T., Matos and J., Reis, Modeling wine preferences by data mining from physicochemical properties, Decis. Support Syst. 47 (2009), pp. 547–553. doi:10.1016/j.dss.2009.05.016
    • (2009) Decis. Support Syst. , vol.47 , pp. 547-553
    • Cortez, P.1    Cerdeira, A.2    Almeida, F.3    Matos, T.4    Reis, J.5
  • 9
    • 84960463485 scopus 로고    scopus 로고
    • Minimum redundancy feature selection from microarray gene expression data
    • C., Ding and H.C., Peng, Minimum redundancy feature selection from microarray gene expression data, Proc. Second IEEE Comput. Syst. Bioinf. Conf. (2003), pp. 523–528.
    • (2003) Proc. Second IEEE Comput. Syst. Bioinf. Conf. , pp. 523-528
    • Ding, C.1    Peng, H.C.2
  • 11
  • 12
    • 1542784498 scopus 로고    scopus 로고
    • Variable selection via nonconcave penalized likelihood and its oracle properties
    • J., Fan and R., Li, Variable selection via nonconcave penalized likelihood and its oracle properties, J. Amer. Statist. Assoc. 96 (2001), pp. 1348–1360. doi:10.1198/016214501753382273
    • (2001) J. Amer. Statist. Assoc. , vol.96 , pp. 1348-1360
    • Fan, J.1    Li, R.2
  • 13
    • 84902449177 scopus 로고    scopus 로고
    • Strong oracle optimality of folded concave penalized estimation
    • J., Fan, L., Xue and H., Zou, Strong oracle optimality of folded concave penalized estimation, Ann. Stat. 42 (2014), pp. 819–849. doi:10.1214/13-AOS1198
    • (2014) Ann. Stat. , vol.42 , pp. 819-849
    • Fan, J.1    Xue, L.2    Zou, H.3
  • 15
    • 33745561205 scopus 로고    scopus 로고
    • An introduction to variable and feature selection
    • I., Guyon and A., Elisseeff, An introduction to variable and feature selection, J. Mach. Learn. Res. 3 (2003), pp. 1157–1182.
    • (2003) J. Mach. Learn. Res. , vol.3 , pp. 1157-1182
    • Guyon, I.1    Elisseeff, A.2
  • 16
    • 27844472191 scopus 로고    scopus 로고
    • An empirical comparison of ensemble methods based on classification trees
    • M., Hamza and D., Larocque, An empirical comparison of ensemble methods based on classification trees, J. Statist. Comput. Simul. 75 (2005), pp. 629–643. doi:10.1080/00949650410001729472
    • (2005) J. Statist. Comput. Simul. , vol.75 , pp. 629-643
    • Hamza, M.1    Larocque, D.2
  • 17
    • 0017947982 scopus 로고
    • Hedonic prices and the demand for clean air
    • D., Harrison and D.L., Rubinfeld, Hedonic prices and the demand for clean air, J. Environ. Econ. Manage. 5 (1978), pp. 81–102. doi:10.1016/0095-0696(78)90006-2
    • (1978) J. Environ. Econ. Manage. , vol.5 , pp. 81-102
    • Harrison, D.1    Rubinfeld, D.L.2
  • 20
    • 16544376973 scopus 로고    scopus 로고
    • Agglomerative hierarchical clustering of continuous variables based on mutual information
    • I., Kojadinovic, Agglomerative hierarchical clustering of continuous variables based on mutual information, Comput. Stat. Data Anal. 46 (2004), pp. 269–294. doi:10.1016/S0167-9473(03)00153-1
    • (2004) Comput. Stat. Data Anal. , vol.46 , pp. 269-294
    • Kojadinovic, I.1
  • 21
    • 85020565290 scopus 로고    scopus 로고
    • Neural network ensembles, cross validation, and active learning, in Advances in Neural Information Processing Systems, Vol. 7, G. Tesauro, D.S. Touretzky and T.K. Leen, eds., MIT Press, Cambridge, 1995, pp. 231–238
    • A., Krogh and J., Vedelsby, Neural network ensembles, cross validation, and active learning, in Advances in Neural Information Processing Systems, Vol. 7, G. Tesauro, D.S. Touretzky and T.K. Leen, eds., MIT Press, Cambridge, 1995, pp. 231–238.
    • Krogh, A.1    Vedelsby, J.2
  • 22
    • 0036127473 scopus 로고    scopus 로고
    • Input feature selection for classification problems
    • N., Kwak and C.H., Choi, Input feature selection for classification problems, IEEE Trans. Neural Netw. 13 (2002), pp. 143–159. doi:10.1109/72.977291
    • (2002) IEEE Trans. Neural Netw. , vol.13 , pp. 143-159
    • Kwak, N.1    Choi, C.H.2
  • 23
    • 34548286564 scopus 로고    scopus 로고
    • Relaxed lasso
    • N., Meinshausen, Relaxed lasso, Comput. Stat. Data Anal. 52 (2007), pp. 374–393. doi:10.1016/j.csda.2006.12.019
    • (2007) Comput. Stat. Data Anal. , vol.52 , pp. 374-393
    • Meinshausen, N.1
  • 24
    • 77958487535 scopus 로고    scopus 로고
    • Stability selection (with discussion)
    • N., Meinshausen and P., Bühlmann, Stability selection (with discussion), J. Royal Statist. Soc:Ser. B 72 (2010), pp. 417–473. doi:10.1111/j.1467-9868.2010.00740.x
    • (2010) J. Royal Statist. Soc: Ser. B , vol.72 , pp. 417-473
    • Meinshausen, N.1    Bühlmann, P.2
  • 25
    • 84871245760 scopus 로고    scopus 로고
    • Ensemble approaches for regression: A survey
    • Article 10
    • J., Mendes-Moreira, C., Soares, A.M., Jorge and J.F., deSousa, Ensemble approaches for regression:A survey, ACM Comput. Surv. 45 (2012), pp. 10. Article 10. doi:10.1145/2379776.2379786
    • (2012) ACM Comput. Surv. , vol.45 , pp. 10
    • Mendes-Moreira, J.1    Soares, C.2    Jorge, A.M.3    deSousa, J.F.4
  • 26
  • 27
    • 84865612777 scopus 로고    scopus 로고
    • An extended variable inclusion and shrinkage algorithm for correlated variables
    • A., Mkhadri and M., Ouhourane, An extended variable inclusion and shrinkage algorithm for correlated variables, Comput. Stat. Data Anal. 57 (2013), pp. 631–644. doi:10.1016/j.csda.2012.07.023
    • (2013) Comput. Stat. Data Anal. , vol.57 , pp. 631-644
    • Mkhadri, A.1    Ouhourane, M.2
  • 28
    • 85027938740 scopus 로고    scopus 로고
    • A group VISA algorithm for variable selection
    • A., Mkhadri and M., Ouhourane, A group VISA algorithm for variable selection, Statist. Methods Appl. 24 (2015), pp. 41–60. doi:10.1007/s10260-014-0281-8
    • (2015) Statist. Methods Appl. , vol.24 , pp. 41-60
    • Mkhadri, A.1    Ouhourane, M.2
  • 29
    • 1942429034 scopus 로고
    • Notes on regression and inheritance in the case of two parents
    • K., Pearson, Notes on regression and inheritance in the case of two parents, Proc. R. Soc. Lond. 58 (1895), pp. 240–242. doi:10.1098/rspl.1895.0041
    • (1895) Proc. R. Soc. Lond. , vol.58 , pp. 240-242
    • Pearson, K.1
  • 30
    • 24344458137 scopus 로고    scopus 로고
    • Feature selection based on mutual information: Criteria of max-dependency, max-relevance and min-redundancey
    • H., Peng, F., Long and C., Ding, Feature selection based on mutual information:Criteria of max-dependency, max-relevance and min-redundancey, IEEE Trans. Pattern Anal. Mach. Intell. 27 (2005), pp. 1226–1238. doi:10.1109/TPAMI.2005.159
    • (2005) IEEE Trans. Pattern Anal. Mach. Intell. , vol.27 , pp. 1226-1238
    • Peng, H.1    Long, F.2    Ding, C.3
  • 31
    • 54949144379 scopus 로고    scopus 로고
    • variable inclusion and shrinkage algorithms
    • P., Radchenko and G.M., James, variable inclusion and shrinkage algorithms, J. Amer. Statist. Assoc. 103 (2008), pp. 1304–1315. doi:10.1198/016214508000000481
    • (2008) J. Amer. Statist. Assoc. , vol.103 , pp. 1304-1315
    • Radchenko, P.1    James, G.M.2
  • 32
    • 84871371181 scopus 로고    scopus 로고
    • Variable selection with error control: another look at stability selection
    • R.D., Shah and R.J., Samworth, Variable selection with error control:another look at stability selection, J. R. Statist. Soc.:Ser. B 75 (2013), pp. 55–80. doi:10.1111/j.1467-9868.2011.01034.x
    • (2013) J. R. Statist. Soc.: Ser. B , vol.75 , pp. 55-80
    • Shah, R.D.1    Samworth, R.J.2
  • 33
    • 84856043672 scopus 로고
    • A mathematical theory of communication
    • 623–656
    • C.E., Shannon, A mathematical theory of communication, Bell Syst. Tech. J. 27 (1948), pp. 379–423.623–656. doi:10.1002/j.1538-7305.1948.tb01338.x
    • (1948) Bell Syst. Tech. J. , vol.27 , pp. 379-423
    • Shannon, C.E.1
  • 34
    • 0001287271 scopus 로고    scopus 로고
    • Regression shrinkage and selection via the lasso
    • R., Tibshirani, Regression shrinkage and selection via the lasso, J. R. Statist. Soc.:Ser. B 58 (1996), pp. 267–288.
    • (1996) J. R. Statist. Soc.: Ser. B , vol.58 , pp. 267-288
    • Tibshirani, R.1
  • 35
    • 79955040218 scopus 로고    scopus 로고
    • Regression shrinkage and selection via the lasso: a retrospective
    • R., Tibshirani, Regression shrinkage and selection via the lasso:a retrospective, J. R. Statist. Soc.:Ser. B (Statist. Methodol.) 73 (2011), pp. 273–282. doi:10.1111/j.1467-9868.2011.00771.x
    • (2011) J. R. Statist. Soc.: Ser. B (Statist. Methodol.) , vol.73 , pp. 273-282
    • Tibshirani, R.1
  • 36
    • 77950210130 scopus 로고    scopus 로고
    • Accurate telemonitoring of Parkinson's disease progression by non-invasive speech tests
    • A., Tsanas, M.A., Little, P.E., McSharry and L.O., Ramig, Accurate telemonitoring of Parkinson's disease progression by non-invasive speech tests, IEEE Trans. Biomed. Eng. 57 (2010), pp. 884–893. doi:10.1109/TBME.2009.2036000
    • (2010) IEEE Trans. Biomed. Eng. , vol.57 , pp. 884-893
    • Tsanas, A.1    Little, M.A.2    McSharry, P.E.3    Ramig, L.O.4
  • 37
    • 77956611003 scopus 로고    scopus 로고
    • mr2PSO: A maximum relevance minimum redundancy feature selection method based on swarm intelligence for support vector machine classification
    • A., Unler, A., Murat and R.B., Chinnam, mr2PSO:A maximum relevance minimum redundancy feature selection method based on swarm intelligence for support vector machine classification, Inf. Sci. 181 (2011), pp. 4625–4641. doi:10.1016/j.ins.2010.05.037
    • (2011) Inf. Sci. , vol.181 , pp. 4625-4641
    • Unler, A.1    Murat, A.2    Chinnam, R.B.3
  • 38
    • 78649238560 scopus 로고    scopus 로고
    • An Improved maximum relevance and minimum redundancy feature selection algorithm based on normalized mutual information, in The International Symposium on Applications and the Internet, Y. Okabe, G. Agha and C. Seon Hong, eds., IEEE Computer Society, Seoul, 2010, pp. 395–398
    • L.T., Vinh, N.D., Thang and Y.K., Lee, An Improved maximum relevance and minimum redundancy feature selection algorithm based on normalized mutual information, in The International Symposium on Applications and the Internet, Y. Okabe, G. Agha and C. Seon Hong, eds., IEEE Computer Society, Seoul, 2010, pp. 395–398.
    • Vinh, L.T.1    Thang, N.D.2    Lee, Y.K.3
  • 39
    • 85020588551 scopus 로고    scopus 로고
    • Variable ranking by solution-path algorithms, M.Math., University of Waterloo (Canada)
    • B., Wang, Variable ranking by solution-path algorithms, M.Math., University of Waterloo (Canada), 2011.
    • (2011)
    • Wang, B.1
  • 41
    • 84890520049 scopus 로고    scopus 로고
    • Use of the zero norm with linear models and kernel methods
    • J., Weston, A., Elisseff, B., Schoelkopf and M., Tipping, Use of the zero norm with linear models and kernel methods, J. Mach. Learn. Res. 3 (2003), pp. 1439–1461.
    • (2003) J. Mach. Learn. Res. , vol.3 , pp. 1439-1461
    • Weston, J.1    Elisseff, A.2    Schoelkopf, B.3    Tipping, M.4
  • 42
    • 84862560560 scopus 로고    scopus 로고
    • Stochastic stepwise ensembles for variable selection
    • L., Xin and M., Zhu, Stochastic stepwise ensembles for variable selection, J. Comput. Graph. Stat. 21 (2012), pp. 275–294. doi:10.1080/10618600.2012.679223
    • (2012) J. Comput. Graph. Stat. , vol.21 , pp. 275-294
    • Xin, L.1    Zhu, M.2
  • 44
    • 84918810308 scopus 로고    scopus 로고
    • RandGA: Injecting randomness into parallel genetic algorithm for variable selection
    • C.-X., Zhang, G.-W., Wang and J.-M., Liu, RandGA:Injecting randomness into parallel genetic algorithm for variable selection, J. Appl. Stat. 42 (2015), pp. 630–647. doi:10.1080/02664763.2014.980788
    • (2015) J. Appl. Stat. , vol.42 , pp. 630-647
    • Zhang, C.-X.1    Wang, G.-W.2    Liu, J.-M.3
  • 45
    • 33845241081 scopus 로고    scopus 로고
    • Darwinian evolution in parallel universes: A parallel genetic algorithm for variable selection
    • M., Zhu and H.A., Chipman, Darwinian evolution in parallel universes:A parallel genetic algorithm for variable selection, Technometrics 48 (2006), pp. 491–502. doi:10.1198/004017006000000093
    • (2006) Technometrics , vol.48 , pp. 491-502
    • Zhu, M.1    Chipman, H.A.2
  • 46
    • 33846114377 scopus 로고    scopus 로고
    • The adaptive lasso and its oracle properties
    • H., Zou, The adaptive lasso and its oracle properties, J. Amer. Statist. Assoc. 101 (2006), pp. 1418–1429. doi:10.1198/016214506000000735
    • (2006) J. Amer. Statist. Assoc. , vol.101 , pp. 1418-1429
    • Zou, H.1
  • 47
    • 16244401458 scopus 로고    scopus 로고
    • Regulzarization variable selection via the elastic net
    • H., Zou and T., Hastie, Regulzarization variable selection via the elastic net, J. R. Statist. Soc.:Ser. B 67 (2005), pp. 301–320. doi:10.1111/j.1467-9868.2005.00503.x
    • (2005) J. R. Statist. Soc.: Ser. B , vol.67 , pp. 301-320
    • Zou, H.1    Hastie, T.2
  • 48
    • 51049104549 scopus 로고    scopus 로고
    • One-step sparse estimates in nonconcave penalized likelihood models
    • H., Zou and R.Z., Li, One-step sparse estimates in nonconcave penalized likelihood models, Ann. Stat. 36 (2008), pp. 1509–1533. doi:10.1214/009053607000000802
    • (2008) Ann. Stat. , vol.36 , pp. 1509-1533
    • Zou, H.1    Li, R.Z.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.